An analyst working for your firm provided an estimated log-linear demand function based on thenatural logarithm of the quantity sold, price, and the average income of consumers. Results aresummarized in the following table:SUMMARY OUTPUTRegression StatisticsMultiple RR SquareAdjusted R SquareStandard ErrorObservationsANOVARegressionResidualTotalInterceptLN PriceLN Incomedf0.9680.9370.9330.00330SSMSF2 0.003637484 0.001818742 202.485980.000242516 8.98206E-0627290.00388Coefficients Standard Error0.570.000.130.51-0.080.15t Stat0.90-19.501.13P-value0.370.000.27Significance F5.55598E-17Lower 95%-0.65-0.09-0.12How would a 4 percent increase in income impact the demand for your product?Demand would increase by 60 percent.Demand would increase by 0.6 percent.Demand would decrease by 60 percent.Demand would decrease by 0.6 percent.Upper 95%1.68-0.070.41

The given regression model is a log-linear regression model in which the dependent and independent…

An analyst working for your firm provided an estimated log-linear demand function based on the natural logarithm of the quantity sold, price, and the average income of consumers. Results are summarized in the following table: SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept LN Price LN Income df 0.968 0.937 0.933 0.003 30 2 27 29 Coefficients 0.51 -0.08 0.15 SS MS F Significance F 0.003637484 0.001818742 202.48598 5.55598E-17 0.000242516 8.98206E-06 0.00388 Standard Error 0.57 0.00 0.13 t Stat 0.90 -19.50 1.13 P-value 0.37 0.00 0.27 Lower 95% -0.65 -0.09 -0.12 How would a 4 percent increase in income impact the demand for your product? Demand would increase by 60 percent. Demand would increase by 0.6 percent. Demand would decrease by 60 percent. Demand would decrease by 0.6 percent. Upper 95% 1.68 -0.07 0.41

An analyst working for your firm provided an estimated log-linear demand function based on the natural logarithm of the quantity sold, price, and the average income of consumers. Results are summarized in the following table: SUMMARY OUTPUT Regression Statistics Multiple R R Square Adjusted R Square Standard Error Observations ANOVA Regression Residual Total Intercept LN Price LN Income df 0.968 0.937 0.933 0.003 30 2 27 29 Coefficients 0.51 -0.08 0.15 SS MS F Significance F 0.003637484 0.001818742 202.48598 5.55598E-17 0.000242516 8.98206E-06 0.00388 Standard Error 0.57 0.00 0.13 t Stat 0.90 -19.50 1.13 P-value 0.37 0.00 0.27 Lower 95% -0.65 -0.09 -0.12 How would a 4 percent increase in income impact the demand for your product? Demand would increase by 60 percent. Demand would increase by 0.6 percent. Demand would decrease by 60 percent. Demand would decrease by 0.6 percent. Upper 95% 1.68 -0.07 0.41

ENGR.ECONOMIC ANALYSIS

14th Edition

ISBN:9780190931919

Author:NEWNAN

Publisher:NEWNAN

Chapter1: Making Economics Decisions

Section: Chapter Questions

Problem 1QTC

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